Telecommunication systems record and maintain operational parameters for billing, performance monitoring, and other related purposes. These operational parameters are often referred to as peg counts. Peg counts typically record the number of times that certain events within the system occur for an interval of time referenced by the peg count. For example, among other values, peg counts are recorded and maintained to indicate the number of messages processed system wide, the number of messages per link, and the number of messages per link set. In some systems, historical peg count data is often maintained for up to seven days in memory, resulting in a large volume of data that must be stored.
Hard disk drives are typically not used for storage of these peg counts and data is often stored in persistent memory. Persistent memory may maintain data through reset cycles for a piece of hardware, but will not preserve data through a power cycle beyond its design duration for power-fault tolerance. The design duration for power-fault tolerance will typically be very short and is typically achieved by use of bulk energy storage capacitors. Persistent memory may preserve data as long as the energy stored in the capacitors can maintain a voltage level at the memory sufficient for the retention of data. When the energy store in the capacitors is depleted to a point that the capacitors cannot maintain the voltage level necessary for the retention of data, the persistent memory will lose its data.
In conventional systems, a single operations, administration, and maintenance (OAM) module with a single persistent memory performs the task of collecting, maintaining and reporting peg counts. The OAM module also handles report generation and distribution to client servers. Based upon the potential for data loss, this single point of failure for peg count collection and storage may no longer be desirable.
Accordingly, in light of these difficulties associated with conventional peg count collection, maintenance and reporting systems, there exists a need for improved methods, systems, and computer program products for detecting and restoring missing or corrupted data in a distributed, scalable, redundant measurement platform database.